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Trusted Research Environments (TREs) offer secure data access but struggle with next-generation research needs like AI and big data. Enhancements are needed for software, automation, and secure export of advanced algorithms.

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TREdata safe havenhealth data analysistrusted research environment

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Area of Science:

  • Health Informatics
  • Data Security
  • Research Methodology

Background:

  • Trusted Research Environments (TREs), also known as Safe Havens, provide secure access to sensitive data for research while maintaining patient confidentiality.
  • Accessing and utilizing sensitive data for research is inherently complex, requiring robust privacy and security measures.

Purpose of the Study:

  • To examine the security measures, administrative procedures, and technical approaches employed by TREs.
  • To identify current capabilities and limitations of TREs in supporting diverse research needs.

Main Methods:

  • Surveyed 73 TRE operators globally, with 22 participating in remote interviews and questionnaires under non-disclosure agreements.
  • Analyzed security processes, administrative procedures, and technical capabilities of participating TREs.

Main Results:

  • TREs demonstrate mature security processes and capabilities for traditional observational studies adhering to the Seven Safes principles.
  • Identified significant limitations in TREs' capacity to support next-generation research, including diverse data types, AI development, big data, and efficient data import/export.

Conclusions:

  • A notable gap exists in software, automation tools, and community knowledge for meeting advanced research requirements within TREs.
  • Exporting AI algorithms and software presents particular disclosure control challenges, necessitating enhanced security measures within TREs.